A Tunable Greedy for Channel Assignment Problem in Cellular Network.

Date of Submission

December 2014

Date of Award

Winter 12-12-2015

Institute Name (Publisher)

Indian Statistical Institute

Document Type

Master's Dissertation

Degree Name

Master of Technology

Subject Name

Computer Science


Advance Computing and Microelectronics Unit (ACMU-Kolkata)


Ghosh, Sasthi Charan (ACMU-Kolkata; ISI)

Abstract (Summary of the Work)

This report presents a probabilistic greedy algorithm for solving the channel assignment problem (CAP) in cellular networks. We took each call as a vertex of a complete edge weighed graph, termed as CAP graph, where an edge weight represents the minimum frequency separation needed between the calls represented by the terminal vertices of that edge. Our objective is to assign non-negative integers representing colors or frequencies to the vertices of the CAP graph such that the required span (maximum frequency - minimum frequency) is minimized while satisfying the frequency separation constraints represented by the edge weights. We begin with a probabilistic ordering of the vertices and apply frequency exhaustive strategy to color them. During the coloring, when color of a vertex exceeds the maximum color of previously allocated vertices, we apply a forced assignment phase to reduce the so far obtained span. Then we propose an iterative compression phase to further reduce the span obtained from applying the frequency exhaustive strategy with forced assignment phase. Finally we introduce a smoothing phase which will try to reduce the higher frequencies obtained by the compression phase with a view to increasing the channel utilization. This essentially helps to cope up with the short term demand fluctuation in a latter phase. It is observed that there is a tradeoff between the computation time and the resulted span. Our proposed algorithm is tunable in a sense that we can get better result by allowing more computation time. The proposed polynomial time algorithm is applied over the well-known benchmark instances and the obtained spans are measured. The obtained results show that the proposed algorithm performs better than the existing assignment strategies with respect to deviation from optimality and/or computation time. The time taken by our algorithm is less than 1.77 seconds (HP Z400 Workstation) even for the most difficult benchmark instances and thus is very much suitable where fast channel assignment is of primary importance while a marginal deviation from optimality may be tolerated.


ProQuest Collection ID: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:28843161

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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.



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